Estimating indirect mortality impacts of armed conflict in civilian populations: panel regression analyses of 193 countries, 1990–2017

Abstract

Background Armed conflict can indirectly affect population health through detrimental impacts on political and social institutions and destruction of infrastructure. This study aimed to quantify indirect mortality impacts of armed conflict in civilian populations globally and explore differential effects by armed conflict characteristics and population groups. Methods We included 193 countries between 1990 and 2017 and constructed fixed effects panel regression models using data from the Uppsala Conflict Data Program and Global Burden of Disease study. Mortality rates were corrected to exclude battle-related deaths. We assessed separately four different armed conflict variables (capturing binary, continuous, categorical, and quintile exposures) and ran models by cause-specific mortality stratified by age groups and sex. Post-estimation analyses calculated the number of civilian deaths. Results We identified 1118 unique armed conflicts. Armed conflict was associated with increases in civilian mortality—driven by conflicts categorised as wars. Wars were associated with an increase in age-standardised all-cause mortality of 81.5 per 100,000 population (β 81.5, 95% CI 14.3–148.8) in adjusted models contributing 29.4 million civilian deaths (95% CI 22.1–36.6) globally over the study period. Mortality rates from communicable, maternal, neonatal, and nutritional diseases (β 51.3, 95% CI 2.6–99.9); non-communicable diseases (β 22.7, 95% CI 0.2–45.2); and injuries (β 7.6, 95% CI 3.4–11.7) associated with war increased, contributing 21.0 million (95% CI 16.3–25.6), 6.0 million (95% CI 4.1–8.0), and 2.4 million deaths (95% CI 1.7–3.1) respectively. War-associated increases in all-cause and cause-specific mortality were found across all age groups and both genders, but children aged 0–5 years had the largest relative increases in mortality. Conclusions Armed conflict, particularly war, is associated with a substantial indirect mortality impact among civilians globally with children most severely burdened.

Implications of armed conflict for maternal and child health: A regression analysis of data from 181 countries for 2000–2019

“…This study may also be limited by the data sources; for example, there may be biases introduced by estimation and data processing by data sources before publication (e.g., WHO or Institute for Health Metrics and Evaluation), which may mask sudden shifts in mortality associated with conflict and produce conservative estimates. However, we have shown previously that such data processing did not obscure abrupt changes in mortality in conflict-affected countries and are unlikely to introduce substantial bias to this analysis [ 19 ]. In terms of outcomes, this study only examined maternal and child mortality, and selective health service indicators.…”

“…They allow changes in health outcomes to be associated with changes in variables such as exposure to conflict over time, whilst adjusting for potential confounders, including country fixed effects and time trends. Although a prospectively written plan is not available, the analysis plan was based on previous conflict and health analytical frameworks developed by the study authors, which included prespecified model structures, covariate selection, and time lags [ 19 ]. We used all available maternal and child health outcomes available, to minimise reporting biases.…”

The association between a conditional cash transfer programme and malaria incidence: a longitudinal ecological study in the Brazilian Amazon between 2004 and 2015

“…These variables would be geographical, historical, or socio-cultural characteristics of each municipality. Fixed effects panel regression is a robust and well-employed method in health systems research and policy evaluation [ 26 ]. A negative binomial specification was chosen as appropriate for modelling count data (e.g.…”

Pediatric Infectious Diseases Encountered During Wartime—Part 1: Experiences and Lessons Learned From Armed Conflict in the Modern Era

“…This report discusses the fluidity of defining “armed conflict,” as well as affirms several international agreements that have promoted the need to protect children from conflict, and offers interventions to “mitigate the effects on children.” A recent systematic review of 155 conflicts from 1945 until the current era underscores the broad definition of the scope of “armed conflict,” ranging from low-intensity and state-sponsored conflict, to all-out war, with dramatic mortality and significant internal and external population displacement [ 4 •]. Basic mortality statistics are well-described in an analysis of 1118 armed conflicts occurring from 1990 to 2017, in 193 countries, which included data from the Global Burden of Disease Study—2017, and the Uppsala Conflict Data Program [ 5 •]. They reported additional mortality of nearly 30 million excess civilian deaths above the baseline levels for these countries over this time period, with a striking additional mortality in children under 5 years of age (263.7 per 100,000) associated with conflict.…”